Predicting Breakdown Pressure Using Filter Cake Models
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Solution Overview
Problem
Conventional hydraulic fracturing simulators fail to accurately predict breakdown pressure due to model simplifications, leading to improper selection of casing, tubing, and pump schedules, which can result in ineffective fracturing operations.
Innovation Solution
The systems and methods account for filter cake buildup by selecting among three breakdown pressure models based on position-and-time-dependent thickness and permeability of the filter cake, and rock formation properties, using models that consider the effects of filter cake on wellbore walls, allowing for more accurate prediction and fracture initiation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional hydraulic fracturing simulators use simplified models to predict breakdown pressure, then the device complexity is reduced and ease of operation is improved, but the measurement precision and reliability of breakdown pressure prediction deteriorate
Solution Approach 1:
The patent changes the parameters considered in breakdown pressure models by incorporating filter cake thickness and permeability as variable parameters that evolve over time. This allows the model to adapt to changing wellbore conditions during drilling, improving prediction accuracy without requiring overly complex formulations. The systematic variation of these parameters through different model configurations enables precise predictions while maintaining reasonable model complexity.
Solution Approach 2:
The patent segments the prediction problem into three distinct models based on filter cake conditions: Model 1 for permeable formations without significant filter cake, Model 2 for impermeable constant-thickness filter cake, and Model 3 for time-dependent filter cake buildup. This segmentation allows each model to be optimized for specific conditions, improving overall prediction accuracy while keeping individual models relatively simple and easy to apply.
2Reliability
If filter cake buildup is accounted for in breakdown pressure prediction, then the reliability of fracturing operation is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent introduces dynamics into the prediction system by making filter cake thickness and permeability time-dependent variables. This allows the model to dynamically adapt to the evolving wellbore conditions as drilling progresses, improving reliability by capturing the transient nature of filter cake buildup. The dynamic approach is implemented through Model 3, which updates predictions based on changing parameters rather than assuming static conditions.
Solution Approach 2:
The patent segments the complex prediction problem into three distinct models that can be selected based on specific wellbore conditions. This segmentation reduces the overall complexity by allowing users to choose the appropriate level of model sophistication for their situation, rather than requiring all users to implement the most complex time-dependent model. Each model captures essential physics appropriate to its intended application.
3Measurement precision
If position-and-time-dependent filter cake properties are used in the model, then the measurement precision of breakdown pressure is improved, but the difficulty of detecting and measuring filter cake properties increases
Solution Approach 1:
The patent applies preliminary action by using filtration experiments conducted on core samples before field application. These experiments establish the relationships between drilling time, filter cake thickness, and permeability for specific formation types. By pre-characterizing these relationships in the laboratory, the patent reduces the difficulty of field measurements while maintaining high prediction precision, as the complex time-dependent behavior has already been captured in controlled experiments.
4Adaptability or versatility
If three different breakdown pressure models are selected based on filter cake properties, then the adaptability of the system to different formation conditions is improved, but the device complexity and model selection complexity increase
Solution Approach 1:
The patent segments the solution space into three distinct models, each optimized for specific formation and filter cake conditions. Model 1 handles permeable formations without significant filter cake, Model 2 handles impermeable constant-thickness filter cake scenarios, and Model 3 handles time-dependent filter cake buildup. This segmentation provides adaptability to different conditions while keeping the selection process manageable through clear criteria for choosing between models.
Solution Approach 2:
The patent uses parameter changes to distinguish between models, primarily based on filter cake permeability and thickness characteristics. By identifying key parameters such as formation permeability, filter cake permeability ratio, and thickness stability, the system adapts to different conditions through parameter-based model selection rather than requiring complex diagnostic procedures. This approach enhances versatility while controlling selection complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables more precise determination of breakdown pressure, optimizing drilling mud weight and improving well productivity by accounting for transient filter cake buildup and fluid flow mechanisms, reducing the risk of under or over-pressurization and enhancing wellbore stability.
Implementation Method 1
a layer of filter cake on a wall of the wellbore... filter cake buildup... position-and-time-dependent thickness and position-and-time-dependent permeability of the filter cake
Implementation Method 2
time-dependent poroelastic model with an impermeable constant-thickness filter cake... time-dependent poroelastic model with time-dependent thickness and permeability filter cake
Data Source
AI summary
Systems and methods for predicting a breakdown pressure of a formation and fracturing the formation account for filter cake effects. The systems and methods measure a time-dependent permeability and a time-dependent thickness of a filter cake formed by a first drilling mud. The systems and methods determine a time-dependent permeability model and a time-dependent thickness model of the filter cake. The systems and methods select a breakdown pressure model based on (i) the time-dependent thickness of the filter cake, (ii) the time-dependent permeability of the filter cake, and (iii) the permeability of the formation. The systems and methods use the selected breakdown pressure model to predict the breakdown pressure of the formation and fracture the formation using a drilling fluid having a mud weight associated with the predicted breakdown pressure of the formation.